@misc{TackKobayashiGaueretal., author = {Tack, Alexander and Kobayashi, Yuske and Gauer, Tobias and Schlaefer, Alexander and Werner, Ren{\´e}}, title = {Bewegungsfeldsch{\"a}tzung in artefaktbehafteten 4D-CT-Bilddaten: Vergleich von paar- und gruppenweiser Registrierung}, series = {21st Annual Meeting of the German-Society-for-Radiation-Oncology}, volume = {Supplement 1}, journal = {21st Annual Meeting of the German-Society-for-Radiation-Oncology}, edition = {191}, publisher = {Springer}, address = {Strahlentherapie und Onkologie}, doi = {10.1007/s00066-015-0847-x}, pages = {65 -- 65}, abstract = {In der Strahlentherapie von Lungentumoren kann mittels Dosisakkumulation der Einfluss von Atembewegungen auf statisch geplante Dosisverteilungen abgesch{\"a}tzt werden. Grundlage sind 4D-CT-Daten des Patienten, aus denen mittels nicht-linearer Bildregistrierung eine Sequenz von Bewegungsfeldern berechnet wird. Typischerweise werden Methoden der paarweisen Bildregistrierung eingesetzt, d.h. konsekutiv zwei Atemphasen aufeinander registriert. Hierbei erfolgt i.d.R. eine physiologisch nicht plausible Anpassung der Felder an CT-Bewegungsartefakte. Gruppenweise Registrierungsans{\"a}tze ber{\"u}cksichtigen hingegen gleichzeitig s{\"a}mtliche Bilddaten des 4D-CT-Scans und erm{\"o}glichen die Integration von zeitlichen Konsistenzbetrachtungen. In diesem Beitrag wird der potentielle Vorteil der gruppen- im Vergleich zur paarweisen Registrierung in artefaktbehafteten 4D-CT-Daten untersucht.}, language = {de} } @inproceedings{TackKobayashiGaueretal., author = {Tack, Alexander and Kobayashi, Yuske and Gauer, Tobias and Schlaefer, Alexander and Werner, Ren{\´e}}, title = {Groupwise Registration for Robust Motion Field Estimation in Artifact-Affected 4D CT Images}, series = {ICART: Imaging and Computer Assistance in Radiation Therapy: A workshop held on Friday 9th October as part of MICCAI 2015 in Munich, Germany. MICCAI workshop. 2015.}, booktitle = {ICART: Imaging and Computer Assistance in Radiation Therapy: A workshop held on Friday 9th October as part of MICCAI 2015 in Munich, Germany. MICCAI workshop. 2015.}, pages = {18 -- 25}, abstract = {Precise voxel trajectory estimation in 4D CT images is a prerequisite for reliable dose accumulation during 4D treatment planning. 4D CT image data is, however, often affected by motion artifacts and applying standard pairwise registration to such data sets bears the risk of aligning anatomical structures to artifacts - with physiologically unrealistic trajectories being the consequence. In this work, the potential of a novel non-linear hybrid intensity- and feature-based groupwise registration method for robust motion field estimation in artifact-affected 4D CT image data is investigated. The overall registration performance is evaluated on the DIR-lab datasets; Its robustness if applied to artifact-affected data sets is analyzed using clinically acquired data sets with and without artifacts. The proposed registration approach achieves an accuracy comparable to the state-of-the-art (subvoxel accuracy), but smoother voxel trajectories compared to pairwise registration. Even more important: it maintained accuracy and trajectory smoothness in the presence of image artifacts - in contrast to standard pairwise registration, which yields higher landmark-based registration errors and a loss of trajectory smoothness when applied to artifact-affected data sets.}, language = {en} }